Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/61610
Title: DNA microarray data clustering by hidden markov models and Bayesian information criterion
Authors: Phasit Charoenkwan
Aompilai Manorat
Jeerayut Chaijaruwanich
Sukon Prasitwattanaseree
Sakarindr Bhumiratana
Keywords: Computer Science
Mathematics
Issue Date: 1-Jan-2006
Abstract: In this study, the microarray data under diauxic shift condition of Saccharomyces Cerevisiae was considered. The objective of this study is to propose another strategy of cluster analysis for gene expression levels under time-series conditions. The continuous hidden markov model was newly proposed to select genes which significantly expressed. Then, new approach of hidden markov model clustering was proposed to include Bayesian information criterion technique which helped to determine the size of model. The result of this technique provided a good quality of clustering from gene expression patterns. © Springer-Verlag Berlin Heidelberg 2006.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=33749419223&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/61610
ISSN: 16113349
03029743
Appears in Collections:CMUL: Journal Articles

Files in This Item:
There are no files associated with this item.


Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.